Generative AI for Developers
Upskilling Course, 16 Academic Hours
Elevate Your Development Game
Why Enroll in this Course?
Generative Artificial Intelligence (AI) is revolutionizing industries by enabling machines to create new content, from compelling text and captivating images to impressive music, all by learning from existing data. This cutting-edge technology empowers developers to innovate like never before, crafting unique user experiences, automating creative processes, and solving complex challenges with ease.
Wawiwa’s Generative AI for Developers Upskilling Course combines theoretical insights with practical skills, empowering you to grasp the core concepts of AI and ML. You’ll learn to apply your knowledge in real-world scenarios, enhancing your coding capabilities with cutting-edge tools like OpenAI and Hugging Face.
By enrolling in this course, you will gain valuable skills in Generative AI and machine learning, and excel in your job as a software developer.
Who should attend?
- Software developers with Python background
![](https://wawiwa-tech.com/wp-content/uploads/2021/06/white-dots.png)
Learning Goals and Outcomes
By the end of the course, participants will:
- Understand and implement AI and ML concepts.
- Create real-world applications with OpenAI and Hugging Face tools.
- Develop and fine-tune generative AI models for various coding tasks.
What You'll Get...
- 16 academic hours of live classes with a professional instructor, teaching in your local language.
- Access to recordings of the sessions, in case you missed one or for reinforcement, for the duration of the course.
- Certificate of Completion, also a digital one for LinkedIn.
- Lifelong membership in Wawiwa’s global alumni community, made of tech professionals that graduated Wawiwa’s reskilling and upskilling programs around the world.
Professional Supervisor
This unique seminar was built by a professional team made up of the leading experts in Software Development and AI, with vast knowledge and experience in training too.
![Maor Mugrabi](https://wawiwa-tech.com/wp-content/uploads/2024/04/Maor-Mugrabi.jpeg)
Maor Mugrabi
Head of AI Courses for Software Developers
![](https://wawiwa-tech.com/wp-content/uploads/2021/06/white-dots.png)
Maor is a data geek deeply passionate about Artificial Intelligence (AI) and Machine Learning (ML).
Maor is dedicated to helping businesses leverage these technologies effectively. Maor is an entrepreneur, managing his own AI/ML development and consultancy firm. Maor’s work has empowered dozens of companies to innovate and grow through custom AI/ML implementations.
He is also a lecturer at John Bryce, where he passes his knowledge and expertise in Machine Learning and Python to his students.
Maor holds a Bachelor’s degree in Applied Mathematics from Bar-Ilan University.
![](https://wawiwa-tech.com/wp-content/uploads/2021/06/white-dots.png)
What Do Graduates Have to Say?
![Ethan Patel](https://wawiwa-tech.com/wp-content/uploads/2024/05/Ethan-Patel.png)
![Benjamin Lee](https://wawiwa-tech.com/wp-content/uploads/2024/05/Benjamin-Lee.png)
Syllabus
Session 1: Introduction to Machine Learning and AI (3 hours)
- AI introduction
- Machine Learning
- Supervised models
- Unsupervised models
- Natural Language Processing
- Computer Vision
- Neural Networks
Session 2: Large Language Models (1 hour)
- What is Generative AI?
- What are Large Language Models?
- Prompting
- Tuning
- Pros and cons of Generative AI compared to the alternatives
Session 3: Open AI workshop - Man in the Middle [Exercise 1] (4 hours)
- Work with Open AI API to:
- Build an LLM question-answering service
- Classification
- Prompt engineering
- Combine everything into a man-in-the-middle service
Session 4: Overview and Q&A (1 hour)
Session 5: Hugging Face, an open-source ocean of pre-trained models (2 hours)
- What is Hugging Face?
- What does it include?
- How to use it?
- Transformers library brief introduction
Session 6: Hugging Face workshop - Cost-reduction with text classification and entity recognitions (4 hours)
- Moving to GPU – Install CUDA, Transformers, and PyTorch
- Replace OpenAI classifier with pre-train open source model
- Apply obfuscation of detected entities
- Leverage confidence scores to build a tailored solution
Session 7: Exercise 2 - overview and Q&A (1 hour)
Interested in more details?
We’d be happy to answer all your questions!
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